Abstract
To analyze airway dimensions throughout the bronchial tree in severe asthmatic patients using multidetector row computed tomography (MDCT) focusing on airway narrowing. Thirty-two patients with severe asthma underwent automated (BronCare software) analysis of their right lung bronchi, with counts of airways >3 mm long arising from the main bronchi (airway count) and bronchial dimension quantification at segmental and subsegmental levels (lumen area [LA], wall area [WA], and WA%). Focal bronchial stenosis was defined as >50% narrowing of maximal LA on contiguous cross-sectional slices. Severe asthmatics were compared to 13 nonsevere asthmatic patients and nonasthmatic (pooled) subjects (Wilcoxon rank tests, then stepwise logistic regression). Finally, cluster analysis of severe asthmatic patients and stepwise logistic regression identified specific imaging subgroups. The most significant differences between severe asthmatic patients and the pooled subjects were bronchial stenosis (subsegmental and all bronchi: P < .002) and WA% (P < .0003). Stepwise logistic regression retained WA% as the only explanatory covariable (P = .002). Two identified clusters of severe asthmatic patients differed for parameters characterizing airway narrowing (airway count: P = .0002; focal bronchial stenosis: P = .009). Airway count was as discriminant as forced expiratory volume in 1 second/forced vital capacity (P = .01) to identify patients in each cluster, with both variables being correlated (r = 0.59, P = .005). Severe asthma-associated morphologic changes were characterized by focal bronchial stenoses and diffuse airway narrowing; the latter was associated with airflow obstruction. WA%, dependent on airway caliber, is the best parameter to identify severe asthmatic patients from pooled subjects.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.